Advancing Quality Control across industries with Machine Learning and OCR

Taymer’s approach to vision based quality control in wire and cable production includes two different facets of artificial intelligence namely machine learning and optical character recognition. 

Taymer’s machine learning approach gives the surface inspection systems a leg up in performing defect detection and classification right in your production line. This technology enables our systems to distinguish between false alarms and genuine defects, providing a more reliable quality assurance report. 

This is made possible by training the software to analyze a diverse range of labeled defect images, to then identify and classify by defect types. These defect types include but are not limited to pinholes, scratches, water spots, discolorations, lumps and neck downs. Training the software in this manner enables it to perform quality inspection in real time during production, guaranteeing that the real defects are immediately flagged for further action.

Taymer’s optical character recognition features enhance print verification (PV) in production lines as your products leave the printer. The optical character recognition in our PV’s reads a wide range of font style and size used on cable print legend.The scanned printed legend is then converted to a machine readable format and included in the quality report.

The key benefits include:

1. Guaranteed accuracy of print legends: Eliminates the potential for human error in setting up and assessing print quality.
2. Improved traceability: verifying date codes and sequential markings for enhanced traceability. 
3. Instantaneous error notification: Provides operators with immediate notifications without additional setup requirements. 

Taymer’s  commitment to precision, reliability and innovation is proven with our technological advancements. Taymer continues to deliver quality control solutions for manufacturing in the wire and cable industry and beyond.